1. Field of the Invention
The invention relates generally to a processing method for image interpolation, and more particularly to a processing method for image interpolation having an edge enhancement effect.
2. Description of Related Art
Nowadays, image enlargement methods can be generally categorized into interpolation methods and super-resolution methods. Conventional interpolation methods include bilinear interpolation and bicubic interpolation, for example, and these interpolation methods are used for different kinds of image enlargement techniques. The computational complexity of the super-resolution methods is higher than the interpolation methods, since the super-resolution methods typically requires a large amount of training sample data to build the enlargement models and to serve as reference for predicting the enlargement of the original image. Therefore, the super-resolution methods require a longer computation period.
Bilinear interpolation methods have found widespread applications today. In a bilinear interpolation method, two neighboring pixels are interpolated in the horizontal and vertical directions in sequence. Although the bilinear interpolation method may be calculated quickly, the lack of high frequency image data results in image blurring after the image enlargement, and a block effect may also be generated.
Bicubic interpolation methods reference the brightness values of four pixels in the original image and multiply the weight values thereof in order to determine the brightness value of interpolation result. Compared to the bilinear interpolation methods, an image enlarged by the bicubic interpolation method has preferable edge sharpness, but as the degree of edge sharpness increases, an overshoot phenomenon at the image edge becomes significant. Moreover, as an enlargement factor is raised, the difference between an image enlarged by the bicubic interpolation method and an image enlarged optically becomes increasingly apparent.